Series.str.replace(pat, repl, n=-1, case=None, flags=0, regex=True)
[source]
Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace()
or re.sub()
.
Parameters: |
pat : string or compiled regex String can be a character sequence or regular expression. New in version 0.20.0: repl : string or callable Replacement string or a callable. The callable is passed the regex match object and must return a replacement string to be used. See New in version 0.20.0: n : int, default -1 (all) Number of replacements to make from start case : boolean, default None
flags : int, default 0 (no flags)
regex : boolean, default True
New in version 0.23.0. |
---|---|
Returns: |
|
Raises: |
ValueError
|
When pat
is a compiled regex, all flags should be included in the compiled regex. Use of case
, flags
, or regex=False
with a compiled regex will raise an error.
When pat
is a string and regex
is True (the default), the given pat
is compiled as a regex. When repl
is a string, it replaces matching regex patterns as with re.sub()
. NaN value(s) in the Series are left as is:
>>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f.', 'ba', regex=True) 0 bao 1 baz 2 NaN dtype: object
When pat
is a string and regex
is False, every pat
is replaced with repl
as with str.replace()
:
>>> pd.Series(['f.o', 'fuz', np.nan]).str.replace('f.', 'ba', regex=False) 0 bao 1 fuz 2 NaN dtype: object
When repl
is a callable, it is called on every pat
using re.sub()
. The callable should expect one positional argument (a regex object) and return a string.
To get the idea:
>>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f', repr) 0 <_sre.SRE_Match object; span=(0, 1), match='f'>oo 1 <_sre.SRE_Match object; span=(0, 1), match='f'>uz 2 NaN dtype: object
Reverse every lowercase alphabetic word:
>>> repl = lambda m: m.group(0)[::-1] >>> pd.Series(['foo 123', 'bar baz', np.nan]).str.replace(r'[a-z]+', repl) 0 oof 123 1 rab zab 2 NaN dtype: object
Using regex groups (extract second group and swap case):
>>> pat = r"(?P<one>\w+) (?P<two>\w+) (?P<three>\w+)" >>> repl = lambda m: m.group('two').swapcase() >>> pd.Series(['One Two Three', 'Foo Bar Baz']).str.replace(pat, repl) 0 tWO 1 bAR dtype: object
Using a compiled regex with flags
>>> regex_pat = re.compile(r'FUZ', flags=re.IGNORECASE) >>> pd.Series(['foo', 'fuz', np.nan]).str.replace(regex_pat, 'bar') 0 foo 1 bar 2 NaN dtype: object
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http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.Series.str.replace.html